Biometric Identification Based on Iris Recognition

Hanaa Mahmood

doi:10.33899/edusj.1970.58949

Abstract

This paper proposes a novel algorithm for the automatic classification of iris images using a 2_D (two Dimension) Variation to estimate the fractal dimensions of the iris. The new technique divided in to three main step. In the first step the segmentation process in iris recognition is used to localize the circular iris and pupil regions, excluding eyelids and eyelashes. The extracted iris region is normalized into a squares block with constant dimensions. In the second step, the feature extraction techniques are improved and implemented. A new feature extraction technique based on a 2_D Variation to estimate the fractal dimensions is used. Finally The Normalized Correlation is used to classify the iris features. The techniques performed with perfect segmentation on a set of 995 iris images of greyscale eye images from MMU database. The as False Accept Rate (FAR) and False Reject Rate (FRR) and (RR) recognition rate are calculated for this technique. The results of the algorithm proved that. The a 2D (two Dimension) Variation to estimate the fractal dimensions method it is a good feature extraction technique. It gives FAR=(1.02) and FRR= (0.52) and a high recognition rate is 98.45%..

Highlights

Biometrics makes use of certain physiological and behavioral characteristics of a person for identification or verification
To obtain the maximum features in the irises, the iris region is normalized to 256 64 for radial and angular resolution for the Fractal Dimension implementation, a preprocessed iris image are divided into blocks.. 128×64 image blocks were obtained from original iris image
Errors are known as False Accept Rate (FAR) and False Reject Rate (FRR) which are given by [22]: FAR

Summary

Introduction

Biometrics makes use of certain physiological and behavioral characteristics of a person for identification or verification. These characteristics are called biometric modalities or traits. The physical characteristics like fingerprints, hand geometry, iris, retina, face, hand vein, facial thermo grams, palm print and behavioral characteristics like signature, voiceprint, gait, keystroke dynamics, etc. Are examples of biometric modalities [10][12]. Using biometrics for identifying and authenticating human beings offers some unique advantages. Biometric authentication bases an identification on an intrinsic part of a human being. Tokens, such as smart cards, magnetic stripe cards, physical keys, and so forth, can be lost, stolen, duplicated, or left at home. Passwords can be forgotten, shared, or observed [20][17]

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Results

Conclusion